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Estimation of sex using dimensions around the metatarsal diaphyseal nutrient foramen: Application of discriminant
Arthur Tsalani Manjatika1, Joshua Gabriel Davimes2, Pedzisai Mazengenya3
1School of Anatomical Sciences, University of the Witwatersrand, Parktown, Johannesburg, South Africa; School of Life Sciences and Allied Health Professions, Anatomy Division, Kamuzu University of Health Sciences, Blantyre, Malawi.
Abstract:
Sex estimation equations are population-specific, and a wider use of multiple bones to generate equations will increase the accuracy of sex estimation in forensic settings. The metatarsal bones have been used previously, however the dimensions around the diaphyseal nutrient foramen have not been utilised in sex estimation. The current study aimed to determine the utility of the dimensions around the nutrient foramen of metatarsal bones in estimating sex in the South Africans of European descent (SAED). Five measurements around the nutrient foramen were taken from a total of 876 metatarsal bones (first to fifth) from 186 individual skeletons (99 males, 87 females) obtained from the Raymond A. Dart Modern Skeletal Collection. Measurements subjected to direct and stepwise discriminant function (DFA) and logistic regression (LRA) analyses included total length, distance from proximal end to nutrient foramen, circumference, and mediolateral and dorsoplantar diameters at the level of the nutrient foramen. The original classification accuracies for multivariable functions of the stepwise and direct DFA ranged from 83.1-88.3% to 85.5-88.3%, respectively. The original classification accuracies for multivariable functions of the stepwise and direct LRA ranged from 83.3%-88.7% to 86.2%-88.3%, respectively. The cross-validation classifications showed a drop of 0-2.4% for DFA and 0.2-1.1% for LRA. The width measurements were better predictors of sex than length. The dimensions around the metatarsal bone nutrient foramen exhibit sexual dimorphism in the SAED. The generated DFA and LRA functions produced high average classification accuracies which are useful in sex estimation during forensic human identification.
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